Method of estimating indoor location of a device

ABSTRACT

A method of estimating indoor location of an electronic device is disclosed. The electronic device will detect multiple Wi-Fi signals, each of which originates from a unique Wi-Fi access point in a building. For each of the signals, the system will determine an access point device identifier and a signal strength indicator, retrieve location coordinates for the access point; and various candidate constants to apply to a distance calculation for determining a distance from the electronic device to each of the access points. The system will repeat the distance calculation multiple times for each of the various constants and determine which constant minimizes a loss value. The system will identify a set of coordinates of the electronic device that are associated with the constant that minimizes the loss value, and then use the coordinates to estimate a location of the electronic device within the building.

BACKGROUND

Methods of determining the location of electronic device have manyapplications. For example, device location can be used to help a mapapplication guide a user to a desired destination, to provide thedevice's user with local weather or safety alerts, or to provide theuser with information that is relevant to the user's location. Morerecently, device location processes have found new applicationsincluding social interaction by social networking apps, and contacttracing to help prevent the spread of infectious disease.

Device location systems typically rely on global positioning system(GPS) signals to identify the device's location. However, GPS signalsare often not reliable when a device is inside of a building. While aGPS signal could be used to determine that a device is within abuilding, it is typically not able to pinpoint the device's locationwithin the building. This is a particular challenge in multi-storybuildings, and/or office buildings that have many rooms.

Existing methods of indoor location tracking are known. Common methodsinclude determining the location between the device and multiple accesspoints by using a free space path loss equation that considers therelative signal strength of the signals received from each access point,or by using a non-linear least squares method. However, these methodsare prone to error, and often cannot determine a precise location of thedevice.

This document describes methods and systems that are directed to solvingat least some of the issues described above.

SUMMARY

In various embodiments, a method of estimating indoor location of anelectronic device is disclosed. A transceiver of an electronic devicethat is in the building will detect multiple Wi-Fi signals, each ofwhich originates from a unique Wi-Fi access point in the building. Foreach of the Wi-Fi signals, the system will process the signal todetermine an access point device identifier and a received signalstrength indicator (RSSI). The system will access a data set of accesspoint data and retrieve location coordinates for the access point. Thesystem will identify various candidate constants to apply to a distancecalculation for determining a distance from the electronic device toeach of the access points, and it will select one of the candidateconstants. The system will estimate a location of the electronic device,and it will use the estimated location of the electronic device and thelocation coordinates in a first calculation for each access point todetermine first distances between the electronic device and each of theaccess points. The system will use the selected constant and the RSSIfor each of the signals in a second calculation to determine seconddistances from the electronic device to each of the access points. Thesystem will applying an error calculation function to the firstdifferences and the second differences to determine a loss value. Thesystem will repeat the determining of first distances, the determiningof second distances, and the determining of a loss value for a pluralityof constants and estimated locations to return additional loss values.The system will use a multilateration function to identify a constantthat minimize the loss values. The system will identify a set ofcoordinates of the electronic device that are associated with theconstant that minimizes the loss value. The system will return the setof coordinates to the electronic device or a remote device for use inestimating a location of the electronic device within the building.

In various embodiments, the error calculation function may includedetermination of a mean square error.

In various embodiments, the second calculation to determine the seconddistances may include a free space path loss equation. The free spaceloss equation may be:

Log(d)=(K−20 Log(f)−RSSI)/20

in which K is the constant; f is the frequency of the detected signal;and RSSI is the signal strength indicator of the access point from whichthe detected signal was received.

In various embodiments, the multilateration function may include anon-linear least squares objective function.

Optionally, the system also may access a data store containingcoordinates for equipment in the building. The system may use thereturned set of coordinates of the electronic device to identify, fromthe data store, an item of equipment having coordinates that areproximate to the returned set of coordinates of the electronic device.The electronic device or a remote computing device may then send acommand to the identified item of equipment to perform a function. Forexample, if the identified item of equipment is a print device, thesystem may command the identified print device to perform a print job.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates an example floor plan of a building having multiplewireless access points, with locations of multiple electronic devices inthe building.

FIG. 2 illustrates data about a wireless access point that an electronicdevice may receive with a signal from the wireless access point.

FIG. 3 illustrates an example of how multilateration may be used todetermine a location of an electronic device.

FIG. 4 illustrates an example of how error can interfere with theaccuracy of a multilateration calculation.

FIG. 5 illustrates an example of a multlateration function.

FIG. 6 illustrates an example location estimation process.

FIG. 7 illustrates components of an example electronic device.

DETAILED DESCRIPTION

As used in this document, the singular forms “a,” “an,” and “the”include plural references unless the context clearly dictates otherwise.Unless defined otherwise, all technical and scientific terms used inthis document have the same meanings as commonly understood by one ofordinary skill in the art. As used in this document, the term“comprising” (or “comprises”) means “including (or includes), but notlimited to.”

In this document, when terms such “first” and “second” are used tomodify a noun, such use is simply intended to distinguish one item fromanother, and is not intended to require a sequential order unlessspecifically stated. The term “approximately,” when used in connectionwith a numeric value, is intended to include values that are close to,but not exactly, the number. For example, in some embodiments, the term“approximately” may include values that are within +/−10 percent of thevalue.

Additional terms that are relevant to this disclosure will be defined atthe end of this Detailed Description section.

This document describes an improved multilateration method forestimating the indoor location of mobile devices. The method can be usedto pinpoint the location of a mobile electronic device that a user iscarrying around the building or that us automatically moving around abuilding. The method can also be used to quickly determine the locationof stationary devices, such as print devices or other equipment, inorder to help maintenance personnel and/or users quickly locate aparticular device within a building. In a building that contains one ormore Wi-Fi networks and multiple network access points, the method canleverage existing equipment and does not require the installation ofadditional location devices such as beacons or cameras positioned withinthe building, or tags that are attached to the electronic device.

FIG. 1 depicts an example floor map 100 of a floor of an officebuilding. The building includes various rooms and corridors, and variouselectronic devices are located within the facility. The electronicdevices may include stationary devices such as print devices 101 andcomputer display devices 103, and/or mobile devices 102 such as mobilephones, laptop computers, or tablet computing devices. The building isequipped with a wireless local area network (WLAN) having any number ofaccess points 117 a-117 c. While three access points are shown in thisimage, this number is only by way of example. Any number of wirelessaccess points may be used, and the total building map may includemultiple floors, each with multiple access points. Each access pointconnects to a router, switch or hub and transmits a Wi-Fi signal to alimited area so that electronic devices that are within the accesspoint's area can communicatively connect to the WLAN via one of theaccess points.

In various embodiments, a system may store a digital representation of afloor map 100 such as that shown. As shown in the example data set ofFIG. 2, the digital representation will include coordinates for eachaccess point (such as x-coordinates 202 and y-coordinates 203), alongwith a unique identifier for each access point such as an alphanumericdevice identification code 201 and/or media access control (MAC) address204. The system may store this information in a table or other datastructure. The system may refer to the access point, and optionally alsoto other map data (such as a room in which each access point islocated), when estimating the location of an electronic device withinthe region of the map, as will be described below.

Each electronic device that connects to the WLAN (such as electronicdevices 101-103 of FIG. 1) will be equipped with a transceiver forwirelessly communicating with the WLAN and or other devices on thenetwork. The transceiver may be configured for any suitablecommunication protocol, including any of the IEEE 802.11 family ofstandards, near-field or short range communication, Bluetooth orBluetooth Low Energy, and/or other protocols.

When an electronic device is located within a building having multipleaccess points, its transceiver may detect more than one access point'ssignal. This is illustrated by way of example in FIG. 3, in which anelectronic device 305 is located within the communication ranges ofaccess points 301, 302 and 303. The x, y coordinates of each accesspoint are known from the data set of FIG. 2. The electronic device 305(or a remote server that is in wireless communication with theelectronic device 305) may determine the location (x, y coordinates) ofthe electronic device 305 by determining the distances d₁, d₁, d₁,between the electronic device 305 and each detected access point 301,302 and 303 for which the electronic device 305 detects a signal.

To enable the determination of distance between the electronic deviceand each access point, the device may measure the signal strength ofeach access point's received signal and store the measurement as areceived signal strength indicator (RSSI). Methods of determining a RSSIfor an access point's signal are known and are common in devices thatemploy IEEE 802.11 communication standards. However, other methods ofmeasuring signal strength may be used, such as known methods ofdetermining a received channel power indicator (RCCI) or Rx level, allof which are intended to be included within the scope of this disclosureas a substitute for RSSI. Most signals have a dynamic range, and signalstrength is not a constant. Therefore, RSSI is typically not measurednot as an instantaneous value, but instead as an average of signalstrength received over a period of time. RSSI may be output as a DCanalog level, represented in terms of milliwatts, decibels per milliwatt(dBM) or another unit of measure. In some systems, RSSI may be anegative number, such as a range of −100 to 0 with zero representing thehighest possible signal strength; in others, RSSI may be a positivenumber, such as a range of 0 to 100 or 0 to 127 with zero representingthe lowest possible signal strength.

In some of the present embodiments, the system may use RSSI to determinethe distance to each access point for which a signal is detected. Asnoted in the Background section of this document, it is known to use afree space path loss equation to measure this distance. However, suchsystems are prone to error. In a known free space loss equation, thedistance d from the electronic device to each access point is determinedas:

Log(d)=(K−20 Log(f)+abs(RSSI))/20

in which:

K is a constant;

f is the frequency of the detected signal; and

RSSI is the signal strength indicator in dBm.

Once the distances between the electronic device and multiple accesspoints are known, a localization algorithm such as min-max,trilateration or multilateration can be used to determine the device'scoordinates. In a multilateration algorithm, each access point'scoordinates (as retrieved from a data set using the access point'sidentifier) will serve as the center of a circle to be drawn around theaccess point. The diameter of the circle will be a function of the RSSI,such that a larger circle reflects a larger signal strength. Theelectronic device's location may be determined at a location where thecircles intersect. For example, the ideal situation of illustrated inFIG. 3 shows that the distances between the electronic device 305 andthe access points 301-303 are approximately equal, and the circlesoverlap.

However, this is not always the case, and while the free space lossalgorithm determines distance, it can result in error. For example, FIG.4 illustrates that in some situations error can result in a “lone accesspoint” 403, in which the signal strength of the access point results ina circle that does not overlap with the circles for the other accesspoints 401, 402. With a lone access point scenario, in theory theelectronic device 405 should not have detected the signal of accesspoint 403. However, since the electronic device 405 actually did detectthe signal of access point 403, error has been introduced into thecalculation.

In some embodiments, the error in a distance calculation can beestimated as a mean square error (MSE), as follows:

${MSE} = \frac{{\Sigma_{i = 1}^{n}\left( {{D1} - {D2}} \right)}^{2}}{n}$

in which:

D1 is the calculated distance from the electronic device to the accesspoint based on the estimated location from the result of themultilateration calculation; and

D2 is the distance to each access point that is calculated using thefree space path loss equation for a given K.

In prior systems, the system may use a nonlinear least squares functionas the multilateration calculation. To do this, the system may firstestimate a possible location of the electronic device using any suitablemethod, such as an average position of the access points (i.e., theinitial Xtest=average of access point x's, and Ytest=average of accesspoint y's). The system may then determine a difference between D1(distance from the electronic device's estimated possible location andeach access point's actual location) and D2 (the distance to each accesspoint that using the free space path loss equation for a given K anddetected RSSI). The system may then determine MSE as the mean of thesquare of the differences for all access points (i.e., the MSEcalculation above). The system may then repeat this for multiplecandidate electronic device locations, varying the possible Xtest, Ytestcoordinates of the electronic device as (until MSE is minimized, usingany suitable minimization algorithm, such as Newton's method of gradientdescent. This is illustrated graphically in FIG. 5, in which threeiterations 501, 502 and 503 of the algorithm are run. In each iteration,three access points are shown, with known coordinates xn, yn positionedin the center of a circle with a diameter d21, d22, d23 that isdetermined based on the detected RSSI of the access point. In iteration501, initial coordinates x, y are estimated, distances d1, d12, d13 fromthose coordinates to each access point are determined, and the MSE iscalculated. In iteration 502, this process is repeated for a differentset of x, y coordinates are selected, and the MSE returned is less thanthat of iteration 501, this continues until the MSE values convergeafter any suitable number of iterations (with convergence—representingloss minimization—shown as iteration 503.

Alternatively, instead of MSE, the system may determine error usinganother function that relies on the distances, such as root mean squareerror, maximum error, mean error, or the like.

The present system improves on prior techniques by varying the constantK in the free space loss equation within various constraints, ratherthan treating K as a fixed constant as in the prior art. This allows thesystem to determine an “optimized K” per access point that minimizesoverall MSE.

In some embodiments, the system selects various values of K that are inthe range of approximately 24 to approximately 28, although other rangesmay be used. The system uses a random initial condition for K for eachaccess point (though other initial conditions can be used, such as theresulting K from the last optimization run). The system then determines,for each access point, the K value that minimizes the MSE distance errorbetween the RSSI calculated distance and the multilateration calculateddistances. This may be illustrated in the following pseudocode, in whichfor any Xtest, Ytest and array of Ks:

newLossFunction(Xtext, Ytest, ArrayOfKs):

-   -   sse=0; mse=0        -   APX=Aps[index].X; APY=Aps[index].Y        -   APRSSI=Aps[index].RSSI; Apfrequency=Aps[index].freq        -   K=ArrayOfKs[index]        -   dFromKandRSSI=10{circumflex over ( )}[[K−(20*log            10(Apfrequency))+abs(APRSSI)]/20]        -   d=sqrt[(Xtest−APX){circumflex over            ( )}2+(Ytest−APY){circumflex over ( )}2]        -   sse=sse+(d−dFromKandRSSI){circumflex over ( )}2    -   mse=sse/(Number of Aps in list of APs)    -   return mse.

in which:

Xtest, Ytest and ArrayOfKs are inputs to the loss function that arevaried to find minimum mse;

APX, APY are known locations of the access point (AP); and

APRSSI and Apfrequency are the signal strength and frequency from eachAP.

The system then selects, for each access point, the K that minimizes theloss, and it uses that K in the free space path loss equation todetermine the distances to each access point. In this scenario, the term“minimize” is the minimization of a scalar function in which the MSEsfor all access point distances are considered, and the K is selected foreach access point that will optimize (i.e., most reduce on a collectivebasis) the loss function in all of the distance calculations. Variousoptimization algorithms may be used, such as Newton's method of gradientdescent as mentioned above, the known Nelder-Mead minimization process(which uses the Simplex algorithm) and the algorithm known as CG, whichuses a nonlinear conjugate gradient algorithm.

This process is further illustrated in the flow diagram of FIG. 6. At601, a transceiver of an electronic device, detecting a multiple ofWi-Fi signals, each of which originates from a unique Wi-Fi access pointin a building. The electronic device, a processor of a remote computingdevice that is in wireless communication with the electronic device, ora combination of the two may execute programming instructions to analyzethe signal and use results of the analysis to determine the coordinatesof the electronic device. The one or more processors will, for each ofWi-Fi signals, analyze the signal to determine an access point deviceidentifier (such as a name and/or MAC address) and a RSSI (step 602). At603, the processor(s) will access a data set of access point data andretrieve location coordinates for each access point. At 60, the systemwill identify multiple candidate constants (i.e., K-values) to apply toa distance calculation for determining a signal strength-based distancefrom the electronic device to each of the access points. At 605, thesystem will estimate a device location for the electronic device. At606, the system will determine distances between the initial devicelocation and each access point. At 607, the system will select acandidate constant to use in a signal strength-based distancecalculation. At 608 the system will use the identified constant and thesignal strength in a distance calculation to determine a distance fromthe electronic device to each of the access points. At 609 the systemwill determine the error between the coordinate-based distance (fromstep 606) and the signal strength based distance (from step 609). At 610the system will repeat steps 605-609 using different estimatedcoordinate values and different constants until the error is minimized.The system will then identify the electronic device coordinates of theiteration in which error is minimized at 611. At 612 the processors willthen return the set of coordinates to the electronic device or a remotedevice for use in estimating a location of the electronic device withinthe building.

The estimation of electronic device location may have any number ofpractical applications. For example, a remote server can use the methodto return a location of a missing or misplaced mobile electronic device,such as a mobile phone, tablet computing device or laptop. The systemcan also be used to identify equipment that is in the building so thatthe electronic device can send commands to operate that equipment (steps613 and 614) For example, f the building includes a network of printdevices, each having a known location stored in a data store, then whenthe mobile electronic device's location is returned the system canaccess the data store's coordinate data to identify the print devicehaving coordinates that are closest to the electronic device's location,and the mobile electronic device or a remote computing device may thenuse a print driver to send a print job to the identified print device sothat the print device can process and print the print job.

FIG. 7 depicts an example of internal hardware that may be included inany of the electronic components of the system, such as any of theelectronic devices 101-103 of FIG. 1, or of a remote server with whichthe electronic devices communicate. An electrical bus 700 serves as aninformation highway interconnecting the other illustrated components ofthe hardware. Processor 705 is a central processing device of thesystem, configured to perform calculations and logic operations requiredto execute programming instructions. As used in this document and in theclaims, the terms “processor” and “processing device” may refer to asingle processor or any number of processors in a set of processors thatcollectively perform a set of operations, such as a central processingunit (CPU), a graphics processing unit (GPU), a remote server, or acombination of these. Read only memory (ROM), random access memory(RAM), flash memory, hard drives and other devices capable of storingelectronic data constitute examples of memory devices 725. A memorydevice may include a single device or a collection of devices acrosswhich data and/or instructions are stored. The memory device may storedata, such as the data set of access point information described above.

An optional display interface 730 may permit information from the bus700 to be displayed on a display device 735 in visual, graphic oralphanumeric format. An audio interface and audio output (such as aspeaker) also may be provided. Communication with external devices mayoccur using various communication devices 740 such as a wirelessantenna, an RFID tag and/or short-range or near-field communicationtransceiver, each of which may optionally communicatively connect withother components of the device via one or more communication system. Thecommunication device 740 may be configured to be communicativelyconnected to a communications network, such as the Internet, a localarea network or a cellular telephone data network.

The hardware may also include a user interface sensor 745 that allowsfor receipt of data from input devices 750 such as a keyboard, a mouse,a joystick, a touchscreen, a touch pad, a remote control, a pointingdevice and/or microphone. The system also may include positional sensors780 such as a global positioning system (GPS) sensor device thatreceives positional data from an external GPS network.

Terminology that is relevant to this disclosure includes:

An “electronic device” or a “computing device” refers to a device orsystem that includes a processor and memory. Each device may have itsown processor and/or memory, or the processor and/or memory may beshared with other devices as in a virtual machine or containerarrangement. The memory will contain or receive programming instructionsthat, when executed by the processor, cause the electronic device toperform one or more operations according to the programminginstructions. Examples of electronic devices include personal computers,laptop computers, digital display devices, print devices, servers,mainframes, virtual machines, containers, gaming systems, televisions,digital home assistants and mobile electronic devices such assmartphones, fitness tracking devices, wearable virtual reality devices,Internet-connected wearables such as smart watches and smart eyewear,personal digital assistants, cameras, tablet computers, laptopcomputers, media players and the like. Electronic devices also mayinclude appliances and other devices that can communicate in anInternet-of-things arrangement, such as smart thermostats,refrigerators, connected light bulbs and other devices. In aclient-server arrangement, the client device and the server areelectronic devices, in which the server contains instructions and/ordata that the client device accesses via one or more communicationslinks in one or more communications networks. In a virtual machinearrangement, a server may be an electronic device, and each virtualmachine or container also may be considered an electronic device. In thediscussion above, a client device, server device, virtual machine orcontainer may be referred to simply as a “device” for brevity.Additional elements that may be included in electronic devices arediscussed above in the context of FIG. 6.

The term “print device” refers to a machine having hardware capable ofreading a digital document file and use the information from the fileand associated print instructions to print of a physical document on asubstrate. Components of a print device typically include a printengine, which includes print hardware such as a print head, which mayinclude components such as a print cartridge containing ink, toner oranother print material, as well as a document feeding system configuredto pass a substrate through the print device so that the print head canprint characters and/or images on the substrate. In some embodiments, aprint device may have additional capabilities such as scanning or faxingand thus may be a multifunction device.

The term “print job” refers to a set of digital data that representstext, images and/or other content that a print device will print on asubstrate

The terms “processor” and “processing device” refer to a hardwarecomponent of an electronic device that is configured to executeprogramming instructions. Except where specifically stated otherwise,the singular terms “processor” and “processing device” are intended toinclude both single-processing device embodiments and embodiments inwhich multiple processing devices together or collectively perform aprocess.

The terms “memory,” “memory device,” “data store,” “data storagefacility” and the like each refer to a non-transitory device on whichcomputer-readable data, programming instructions or both are stored.Except where specifically stated otherwise, the terms “memory,” “memorydevice,” “data store,” “data storage facility” and the like are intendedto include single device embodiments, embodiments in which multiplememory devices together or collectively store a set of data orinstructions, as well as individual sectors within such devices.

In this document, the terms “communication link” and “communicationpath” mean a wired or wireless path via which a first device sendscommunication signals to and/or receives communication signals from oneor more other devices. Devices are “communicatively connected” if thedevices are able to send and/or receive data via a communication link.“Electronic communication” refers to the transmission of data via one ormore signals between two or more electronic devices, whether through awired or wireless network, and whether directly or indirectly via one ormore intermediary devices.

The features and functions described above, as well as alternatives, maybe combined into many other different systems or applications. Variousalternatives, modifications, variations or improvements may be made bythose skilled in the art, each of which is also intended to beencompassed by the disclosed embodiments.

1. A method of estimating indoor location of an electronic device, the method comprising: by a transceiver of an electronic device, detecting a plurality of Wi-Fi signals, each of which originates from a unique Wi-Fi access point in a building; and by one or more processors: for each of the plurality of Wi-Fi signals: analyzing the signal to determine an access point device identifier and a received signal strength indicator (RSSI); and accessing a data set of access point data and retrieve location coordinates for the access point, identifying a plurality of candidate constants to apply to a distance calculation for determining a distance from the electronic device to each of the access points, selecting a constant from the plurality of candidate constants, estimating a location of the electronic device, using the estimated location of the electronic device and the location coordinates in a first calculation for each access point to determine first distances between the electronic device and each of the access points, using the selected constant and the RSSI for each of the signals in a second calculation to determine second distances from the electronic device to each of the access points, applying an error calculation function to the first differences and the second differences to determine a loss value, repeating the determining of first distances, the determining of second distances, and the determining of a loss value for a plurality of constants and estimated locations to return additional loss values, using a multilateration function to identify a constant that minimize the loss values, identifying a set of coordinates of the electronic device that are associated with the constant that minimizes the loss value, and returning the set of coordinates to the electronic device or a remote device for use in estimating a location of the electronic device within the building.
 2. The method of claim 1, wherein the error calculation function comprises determination of a mean square error.
 3. The method of claim 1, wherein the second calculation to determine the second distances comprises a free space path loss equation.
 4. The method of claim 3, in which the free space loss equation comprises: Log(d)=(K−20 Log(f)−RSSI)/20 in which: K is the selected constant, f is the frequency of the detected signal, and RSSI is the signal strength indicator of the access point from which the detected signal was received.
 5. The method of claim 1, wherein the multilateration function comprises a non-linear least squares objective function.
 6. The method of claim 1, further comprising: accessing a data store containing coordinates for equipment in the building; using the returned set of coordinates of the electronic device to identify, from the data store, an item of equipment having coordinates that are proximate to the returned set of coordinates of the electronic device; and sending a command to the identified item of equipment to perform a function.
 7. The method of claim 6, wherein: the identified item of equipment is a print device; and the function is printing a print job.
 8. A system for estimating indoor location of an electronic device, the system comprising: an electronic device comprising a transceiver; and one or more processors; and a memory device containing programming instructions that are configured to cause the one or more processors to: determine that the transceiver has detected a plurality of Wi-Fi signals, each of which originated from a unique Wi-Fi access point in a building, for each of the plurality of Wi-Fi signals: analyze the signal to determine an access point device identifier and a received signal strength indicator (RSSI); and access a data set of access point data and retrieve location coordinates for the access point, and identify a plurality of candidate constants to apply to a distance calculation for determining a distance from the electronic device to each of the access points, select a constant from the plurality of candidate constants, estimate a location of the electronic device, use the estimated location of the electronic device and the location coordinates in a first calculation for each access point to determine first distances between the electronic device and each of the access points, use the selected constant and the RSSI for each of the signals in a second calculation to determine second distances from the electronic device to each of the access points, apply an error calculation function to the first differences and the second differences to determine a loss value, repeat the determining of first distances, the determining of second distances, and the determining of a loss value for a plurality of constants and estimated locations to return additional loss values, use a multilateration function to identify a constant that minimize the loss values, identify a set of coordinates of the electronic device that are associated with the constant that minimizes the loss value, and return the set of coordinates to the electronic device or a remote device for use in estimating a location of the electronic device within the building.
 9. The system of claim 8, wherein the error calculation function comprises determination of a mean square error, and the second calculation to determine the second distances comprises a free space path loss equation.
 10. The system of claim 9, in which the free space loss equation comprises: Log(d)=(K−20 Log(f)−RSSI)/20 in which: K is the selected constant, f is the frequency of the detected signal, and RSSI is the signal strength indicator of the access point from which the detected signal was received.
 11. The system of claim 8, wherein the multilateration function comprises a non-linear least squares objective function.
 12. The system of claim 8, further comprising: a data store containing coordinates for equipment in the building; and additional programming instructions that are configured to cause the one or more processors to: access the data store, use the returned set of coordinates of the electronic device to identify, from the data store, an item of equipment having coordinates that are proximate to the returned set of coordinates of the electronic device, and send a command to the identified item of equipment to perform a function.
 13. The system of claim 12, wherein: the item of equipment is a print device; and the function is printing a print job.
 14. The system of claim 12, wherein the one or more processors are each components of the electronic device.
 15. The system of claim 12, wherein the one or more processors comprise: at least one processor that is a component of the electronic device; and at least one processor that is a component of a remote computing device that is in communication with the electronic device.
 16. A computer-readable medium containing programming instructions that are configured cause one or more processors to estimate indoor location of an electronic device by: determining that a transceiver of the electronic device has detected a plurality of Wi-Fi signals, each of which originated from a unique Wi-Fi access point in a building; and for each of the plurality of Wi-Fi signals: analyzing the signal to determine an access point device identifier and a received signal strength indicator (RSSI), and accessing a data set of access point data and retrieve location coordinates for the access point; identifying a plurality of candidate constants to apply to a distance calculation for determining a distance from the electronic device to each of the access points; selecting a constant from the plurality of candidate constants; estimating a location of the electronic device; using the estimated location of the electronic device and the location coordinates in a first calculation for each access point to determine first distances between the electronic device and each of the access points; using the selected constant and the RSSI for each of the signals in a second calculation to determine second distances from the electronic device to each of the access points; applying an error calculation function to the first differences and the second differences to determine a loss value; repeating the determining of first distances, the determining of second distances, and the determining of a loss value for a plurality of constants and estimated locations to return additional loss values; using a multilateration function to identify a constant that minimize the loss values; identifying a set of coordinates of the electronic device that are associated with the constant that minimizes the loss value; and returning the set of coordinates to the electronic device or a remote device for use in estimating a location of the electronic device within the building.
 17. The computer-readable medium of claim 16, wherein: the error calculation function comprises determination of a mean square error; and the second calculation to determine the second distances comprises a free space path loss equation.
 18. The computer-readable medium of claim 17, in which the free space loss equation comprises: Log(d)=(K−20 Log(f)−RSSI)/20 in which: K is the selected constant, f is the frequency of the detected signal, and RSSI is the signal strength indicator of the access point from which the detected signal was received.
 19. The computer-readable medium of claim 17, wherein the multilateration function comprises a non-linear least squares objective function. 